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Titlebook: Biomedical Image Registration; 8th International Wo Stefan Klein,Marius Staring,Stefan Sommer Conference proceedings 2018 Springer Nature S

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Consolidation of Axiomatic Set Theory0.89 ± 0.53 mm. Additionally, a number of automatically obtained clinical measures were compared to ground truth values. On average we obtained a Pearson’s correlation coefficient (.) of 0.94 (0.99–0.74).
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Semi-automated Processing of Real-Time CMR Scans for Left Ventricle Segmentation0.89 ± 0.53 mm. Additionally, a number of automatically obtained clinical measures were compared to ground truth values. On average we obtained a Pearson’s correlation coefficient (.) of 0.94 (0.99–0.74).
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Adaptive Graph Diffusion Regularisation for Discontinuity Preserving Image Registratione graph, we develop an adaptive edge weight function to detect sliding boundaries. We implement the adaptive graph diffusion regularisation method in the Demons registration framework. The presented method is tested on synthetic 2D images and on the public 4D-CT DIR-Lab data set, where we are able to correctly detect the sliding organ boundaries.
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0302-9743 n, The Netherlands, in June 2018...The 11 full and  poster papers included in this volume were carefully reviewed and selected from 17 submitted papers. The papers are organized in the following topical sections: Sliding Motion, Groupwise Registration, Acceleration, and Applications and Evaluation..
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An Inhomogeneous Multi-resolution Regularization Concept for Discontinuity Preserving Image Registrawhich prefers transformations which are explained in lower resolution levels. For an early proof of concept we analyze the registration performance of our method on synthetic 2D data and on a 2D slice of the POPI model.
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